Review of Machine Learning Techniques in Anemia Recognition
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



Research Paper | Computer Science & Engineering | Saudi Arabia | Volume 2 Issue 3, March 2013

Review of Machine Learning Techniques in Anemia Recognition

Jameela Ali Akrimi, Abdul Rahim Ahmad, Loay E. George

Machine learning procedure offers a major platform in cases where a model lacks and the amount of data is enormous in explaining the relation and the generation of the data that is set. A research on trends and application of machine learning such as algorithms, techniques, and methods present practical functions for problem solving and application of techniques in settling and automatic data extraction. Anemia is one of the common diseases affecting individuals worldwide. In this study, due to lack of a distinct models, an artificial neural network (ANN) and support vector machines (SVM) have been put in place to establish a non linear function that is continuous and expresses the interdependency of the data collected and erythrocytes levels. This study will identify the use of artificial neural networks, support vector machines and statistical models and methods in the recognition of iron deficiency that leads to anemic conditions.

Keywords: Artificial neural networks, support vector machines, statistical models

Edition: Volume 2 Issue 3, March 2013

Pages: 140 - 142

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How to Cite this Article?

Jameela Ali Akrimi, Abdul Rahim Ahmad, Loay E. George, "Review of Machine Learning Techniques in Anemia Recognition", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=IJSRON2013370, Volume 2 Issue 3, March 2013, 140 - 142

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